ZnO Nanorod Integrated Flexible Carbon Fibers for Sweat Cortisol Detection

https://pubs.acs.org/doi/abs/10.1021/acsaelm.9b00730

Authors:  Sekar Madhu, Allen Joseph,  Anthuuvan Sriramprabha RamasamyPandiaraj Manickam*Shekhar BhansaliPonpandian NagamonyViswanathan Chinnuswamy*

Abstract

Sensors fabricated on fabrics provide an elevated ease of use for wearable sensors. Such sensors will play a critical role in detecting the elevations in the concentrations of biochemical markers in human sweat. The ability of making such measurements is becoming an important tool for non-invasive and real-time health monitoring. We present a yarn-based flexible and superwettable electrochemical immunosensing strategy for highly selective and sensitive detection of cortisol in sweat. ZnO nanorods (ZnONRs)-coated flexible carbon yarns were prepared by using a hydrothermal method for immobilizing specific anti-cortisol antibodies and used as an immunosensing platform for detecting sweat cortisol levels. The morphology, elemental composition, crystallinity, and specific surface area were analyzed by using analytical techniques such as transmission electron microscopy (TEM), field emission scanning electron microscopy coupled energy-dispersive X-ray analysis (FE-SEM/EDS), X-ray diffraction (XRD), fourier-transform infrared spectroscopy (FT-IR), Raman spectroscopy, and Brunauer–Emmett–Teller (BET) analysis. The ZnONRs integrated carbon yarns showed excellent mechanical stability and superwettable properties. The immunosensor exhibited a wide linear detection range from 1 fg/mL to 1 μg/mL. The detection limits of the immunosensor were calculated to be between 0.45 and 0.098 fg/mL by using CV and DPV techniques, respectively. Additionally, cell viability studies were performed to investigate the biocompatibility and cytotoxicity of this carbon yarn ZnO sensing platform. The immunosensor was applied to measure the cortisol concentration in human sweat samples, and the outcomes were validated by using a chemiluminescent immunoassay system

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